Maria Athelogou

Cognition Network Technology: Object Orientation and Fractal Topology in Biomedical Image Analysis. Method and Applications

Data analysis in general and image analysis in particular require multi-scale approaches when dealing with complex structures. Relational information between structures on different scales needs to be taken into account. In many application fields, automated image interpretation still is a significant bottleneck due to the lack of appropriate image analysis technology. A new approach, Cognition Network Technology, is presented that was developed to handle and analyze complex data. This contribution focuses on how it handles and analyzes image data based on an object oriented, hierarchical and networked data model. A specific programming language allows building a semantic knowledge base that is used to interpreting image data by creating and processing instances of this data model. In many operational analysis tasks the approach has proven to produce reliable results fully automatically. It especially extracts structures of interest even in challenging cases such as low signal to noise ratio images, heterogeneous or variable structures of interest or tasks which include a complex semantic.

Bildanalyse in Medizin und Biologie

Heutzutage sind bildgebende Verfahren aus medizinischen Untersuchungen nicht mehr wegzudenken. Diverse Methoden – basierend auf dem Einsatz von Ultraschallwellen, Rontgenstrahlung, Magnetfeldern oder Lichtstrahlen – werden dabei spezifisch eingesetzt und liefern umfangreiches Datenmaterial uber den Korper und sein Inneres. Anhand von Mikroskopieaufnahmen aus Biopsien konnen daruber hinaus Daten uber die morphologische Eigenschaften von Korpergeweben gewonnen werden. Aus der Analyse all dieser unterschiedlichen Arten von Informationen und unter Konsultation weiterer klinischer Untersuchungen aus diversen medizinischen Disziplinen kann unter Berucksichtigung von Anamnesedaten ein „Gesamtbild“ des Gesundheitszustands eines Patienten erstellt werden. Durch die Flut der erzeugten Bilddaten kommt der Bildverarbeitung im Allgemeinen und der Bildanalyse im Besonderen eine immer wichtigere Rolle zu. Gerade im Bereich der Diagnoseunterstutzung, der Therapieplanung und der bildgefuhrten Chirurgie bilden sie Schlusseltechnologien, die den Forschritt nicht nur auf diesen Gebieten masgeblich vorantreiben.

Cognition Network Technology for Automated Holistic Analysis in Mammography

Digital mammography and comprehensive breast cancer screening approaches have led to the generation of a vast amount of image data. Since the visual inspection of a large set of images is expensive and to some extend also subjective, new methods for fully automated mammography image analysis are needed. The Definiens Cognition Network Technology (CNT) solves the image analysis problem by simulating human cognition processes using knowledge based and context dependent processing. It represents processed image data, image processing methods, and image objects and their definitions in a unified model which incorporates elements from semantic networks, description logics and functional programming. We present first steps towards a successful application of this technology on automated detection of masses and calcifications according to the ACR BI-RADS™ standard.